Spectral Analysis for Univariate Time Series

Author:   Donald B. Percival (University of Washington) ,  Andrew T. Walden (Imperial College London)
Publisher:   Cambridge University Press
ISBN:  

9781107028142


Pages:   780
Publication Date:   19 March 2020
Format:   Hardback
Availability:   In stock   Availability explained
We have confirmation that this item is in stock with the supplier. It will be ordered in for you and dispatched immediately.

Our Price $194.04 Quantity:  
Add to Cart

Share |

Spectral Analysis for Univariate Time Series


Add your own review!

Overview

Full Product Details

Author:   Donald B. Percival (University of Washington) ,  Andrew T. Walden (Imperial College London)
Publisher:   Cambridge University Press
Imprint:   Cambridge University Press
Dimensions:   Width: 18.20cm , Height: 4.30cm , Length: 25.90cm
Weight:   1.440kg
ISBN:  

9781107028142


ISBN 10:   1107028140
Pages:   780
Publication Date:   19 March 2020
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Hardback
Publisher's Status:   Active
Availability:   In stock   Availability explained
We have confirmation that this item is in stock with the supplier. It will be ordered in for you and dispatched immediately.

Table of Contents

1. Introduction to spectral analysis; 2. Stationary stochastic processes; 3. Deterministic spectral analysis; 4. Foundations for stochastic spectral analysis; 5. Linear time-invariant filters; 6. Periodogram and other direct spectral estimators; 7. Lag window estimators; 8. Combining direct spectral estimators; 9. Parametric spectral estimators; 10. Harmonic analysis; 11. Simulation of time series.

Reviews

'Percival and Walden have written an excellent text for anyone who analyzes or wants to learn how to analyze time series data in the frequency domain. The aims and scope of the text are broad and require the skills that one would acquire in a basic course on mathematical statistics. The authors take a data analysis approach and relegate theoretical material to special sections or problems, and give ample references to the more theoretical details. The authors give philosophical as well as practical guidance in applying spectral techniques to time series data. This book is one of the best texts on the topic and would be useful as a reference for researchers. In addition, the book would be great as a textbook for a one semester/quarter course on the spectral analysis of time series.' David Stoffer, University of Pittsburgh 'I used the first edition of the book several times for my spectral analysis courses. It was an excellent addition to the literature. This new edition, considerably enlarged, will certainly have the same impact as the first. The authors should be congratulated for a most valuable book.' Pedro A. Morettin, Universidade de Sao Paulo 'Spectral Analysis for Univariate Time Series is an excellent step-by-step introduction to using Fourier methods in the statistical analysis of time series. The in-depth material, extensive exercises, practical advice, and illustrative data analyses provide valuable insights to readers of varied backgrounds.' Peter F. Craigmile, Ohio State University 'This book will serve scientists and engineers in many fields with a general toolbox for spectral analysis. The fundamentals of non-parametric and parametric methods are presented, together with convincing examples and exercises. I especially appreciate the extensive chapter on combining direct spectral estimators, as todays standard toolbox definitely should include multitaper based spectral analysis.' Maria Sandsten, Lunds universitet `Percival and Walden have written an excellent text for anyone who analyzes or wants to learn how to analyze time series data in the frequency domain. The aims and scope of the text are broad and require the skills that one would acquire in a basic course on mathematical statistics. The authors take a data analysis approach and relegate theoretical material to special sections or problems, and give ample references to the more theoretical details. The authors give philosophical as well as practical guidance in applying spectral techniques to time series data. This book is one of the best texts on the topic and would be useful as a reference for researchers. In addition, the book would be great as a textbook for a one semester/quarter course on the spectral analysis of time series.' David Stoffer, University of Pittsburgh `I used the first edition of the book several times for my spectral analysis courses. It was an excellent addition to the literature. This new edition, considerably enlarged, will certainly have the same impact as the first. The authors should be congratulated for a most valuable book.' Pedro A. Morettin, Universidade de Sao Paulo `Spectral Analysis for Univariate Time Series is an excellent step-by-step introduction to using Fourier methods in the statistical analysis of time series. The in-depth material, extensive exercises, practical advice, and illustrative data analyses provide valuable insights to readers of varied backgrounds.' Peter F. Craigmile, Ohio State University `This book will serve scientists and engineers in many fields with a general toolbox for spectral analysis. The fundamentals of non-parametric and parametric methods are presented, together with convincing examples and exercises. I especially appreciate the extensive chapter on combining direct spectral estimators, as todays standard toolbox definitely should include multitaper based spectral analysis.' Maria Sandsten, Lunds universitet


Author Information

Donald B. Percival is the author of 75 publications in refereed journals on a variety of topics, including analysis of environmental time series, characterization of instability of atomic clocks and forecasting inundation of coastal communities due to trans-oceanic tsunamis. He is the co-author (with Andrew Walden) of Spectral Analysis for Physical Applications: Multitaper and Conventional Univariate Techniques (Cambridge, 1993) and Wavelet Methods for Time Series Analysis (Cambridge, 2000). He has taught graduate-level courses on time series analysis, spectral analysis and wavelets for over thirty years at the University of Washington. Andrew T. Walden has authored 100 refereed papers in scientific areas including statistics, signal processing, geophysics, astrophysics and neuroscience, with an emphasis on spectral analysis and time series methodology. He worked in geophysical exploration research before joining Imperial College London. He is co-author (with Donald B. Percival) of Spectral Analysis for Physical Applications: Multitaper and Conventional Univariate Techniques (Cambridge,1993) and Wavelet Methods for Time Series Analysis (Cambridge, 2000). He has taught many courses including time series, spectral analysis, geophysical data analysis, applied probability and graphical modelling, primarily at Imperial College London, and also at the University of Washington.

Tab Content 6

Author Website:  

Customer Reviews

Recent Reviews

No review item found!

Add your own review!

Countries Available

All regions
Latest Reading Guide

 

MD

Shopping Cart
Your cart is empty
Shopping cart
Mailing List